Businesses often struggle to get the complete story from their market research – even when using a mix of methodologies. Qualitative methods give rich, detailed insights but are limited in size. Quantitative research offers scale but doesn’t dig into the reasons behind consumer choices. Big Qual bridges this gap.
It provides a deep understanding of consumer motivations that qualitative research delivers, combined with the broader reach of quantitative studies, all in a cost-effective and efficient way.
Frank Kelly, Market Research Practice Lead at Virtual Incentives, explains that Big Qual combines the best of both approaches.
“Big qual tries to make a more systematic and quantitative approach to understanding the why and how of decision-making,” Frank says.
The result is a market research methodology that’s more scalable than traditional qualitative research, with a lower cost and a faster turnaround. It’s an innovative approach that is poised to have a big effect on how data is gathered.
What is Big Qual?
Big Qual is a hybrid market research methodology that combines certain elements of both qualitative and quantitative research. It uses advanced technologies, particularly artificial intelligence, to analyze open-ended responses from larger groups of participants than traditional qualitative studies.
Researchers can gather rich, detailed information from a broader sample, potentially leading to more representative findings using Big Qual.
The growth of big qual is closely tied to the development of agile research platforms. These platforms leverage AI and cloud computing to help researchers conduct and analyze larger qualitative studies efficiently.
They can quickly gather, analyze, and summarize large amounts of qualitative data, offering insights that were previously difficult or impossible to obtain at scale.
Comparing market research methodologies
Comparing Big Qual with traditional research methods helps understand what makes it different.
Qualitative research typically involves small groups of 10-20 participants. It’s often expensive, with costs around $100-$200 per interview. The process involves scheduling, briefing moderators, and summarizing data.
As a result, these projects are usually done on a smaller scale. Studies provide in-depth insights but may not be representative of larger populations.
Quantitative research uses large samples, often 500-1000+ participants. It’s relatively inexpensive, usually costing $3-5 per survey. While this method provides statistically significant data, it often lacks the depth needed to fully understand consumer behavior.
Big Qual is not meant to replace either method. It’s a hybrid of qualitative and quantitative research.
Typically, it involves about 100 participants and costs around $15 per interview. This method allows for more detailed responses than typical quantitative surveys while providing a larger sample size than traditional qualitative studies.
Researchers can scale qualitative research while maintaining depth using AI technologies. AI tools can summarize open-ended responses, conduct interviews through chatbots, and assist with moderating online focus groups.
These tools allow researchers to collect more data without the high costs associated with traditional methods.
“The price is much lower per interview, allowing for significantly larger sample sizes, similar to quantitative surveys,” Frank says.
The benefits of Big Qual
One of the biggest challenges with traditional qualitative research is the high cost per interview.
Costs can increase in specific industries like healthcare or B2B markets, where participants are harder to reach. Qualitative research often involves a lot of human effort. Scheduling interviews, briefing moderators, and analyzing the data all take time and resources.
Big Qual tackles these issues by using AI to handle many of the tasks that traditionally require human effort. AI can summarize open-ended responses, conduct interviews asynchronously, and even assist with probing during interviews.
Researchers can then collect insights from a larger group of participants without the logistical burden. The method combines the richness of qualitative data with the efficiency of quantitative research.
And the approach doesn’t sacrifice data quality. Big qual allows researchers to gather actionable insights while keeping costs manageable.
Using Big Qual methodologies, companies can afford to conduct studies with hundreds of participants, offering more representative data while going more in-depth than a traditional quantitative survey.
Challenges in Big Qual
Despite its advantages, Big Qual still faces challenges.
One of the key obstacles is finding the right participants. In traditional qualitative research, participants are carefully vetted to ensure they meet specific criteria. They need to be articulate, reliable, and capable of providing thoughtful responses.
Quantitative research, on the other hand, often relies on large panels of respondents, but the vetting process is less rigorous. As a result, participants may not provide the same depth of insight.
Researchers need participants willing to engage in more demanding tasks to make big qual effective. These tasks could include video interviews, submitting photos or videos of their daily lives, or participating in online discussions.
Read More: How to Choose the Right Incentives for Your Focus Groups
Companies focus on pre-profiling respondents to ensure they are a good fit for these activities. Pre-profiling helps avoid the frustration of participants not qualifying for a study, which can lead to poor data quality.
The future of market research methodologies
Big Qual has the potential to change how researchers approach and run studies.
One future possibility is using big qual to develop longitudinal qualitative tracking. In quantitative research, trackers are commonly used to measure changes in consumer behavior over time.
A shift to longitudinal qualitative tracking would allow companies to gather insights continuously rather than through one-off projects. Businesses could conduct 50 in-depth interviews every month over time, asking similar questions and following trends.
By doing this, companies could obtain more nuanced data on how consumer opinions change over time. It could also help brands adapt their strategies more quickly by providing real-time insights into shifts in consumer behavior.
Behavioral targeting is another promising area for Big Qual. Tracking consumers’ real-world behaviors, such as their online purchases or browsing habits, would enable researchers to build more accurate profiles.
Why Big Qual matters for businesses
Big Qual offers a powerful solution for companies that want a deeper understanding of their customers. It combines the depth of qualitative research with the scale and efficiency of quantitative methods. Big qual allows businesses to gather more detailed insights without the high costs and time constraints of traditional qualitative market research methodologies.
“Big qual doesn’t replace qualitative or quantitative research—it stands in the gap between them,” says Frank. “It allows us to extend the learnings from qual, refine them, and then move into quant with a much clearer picture of what we need to ask.”
Big Qual isn’t just another trend—it helps companies gain deeper insights into their consumers. The method scales qualitative research without losing the richness of the data. Whether refining a product or testing a strategy, Big Qual delivers insights that lead to impactful decisions.
Learn more about incentives for survey participants.